Taylor Veale
A collaborative learning strategy for model-free control of an array of wave energy converters.
Rel. Giovanni Bracco. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022
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Abstract
Ocean energy is an abundant but relatively unexploited renewable energy source which has the potential to become one of the key players in the upscaling of global renewable energy production for the near future. Despite this huge potential, ocean energy technology and especially wave energy technology is still considered to be immature compared to other renewable energy technologies. One of the main goals to be achieved is to reduce the levelized cost of electricity (LCOE) coming from wave energy converter devices in order to make them economically competitive with respect to other more established renewable energy sources. To achieve this, one of the main areas of focus in recent years has been to develop and optimise control strategies to improve the efficiency of the energy conversion process.
The main challenges that wave energy converters (WECs) face, stem from the irregular reciprocating nature of the energy source, making the design of the control strategy, the WEC itself, and any modelling of the WEC-wave interaction extremely challenging
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